Evidence map›Paper›PMID 42569757›Full record

ArticlePhysical review research

Exactly solvable statistical physics models for large neuronal populations.

Christopher W Lynn, Qiwei Yu, Rich Pang, William Bialek, Stephanie E Palmer

Abstract read
In one paragraph

Article in Physical review research. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Quantifying the compressibility of the human brain.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  5. Article
  6. Statistical physics of large-scale neural activity with loops.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  7. Article
  8. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Christopher W LynnDepartment of Physics, Quantitative Biology Institute, and Wu Tsai Institute, Yale University, New Haven, Connecticut 06520, USA.ORCID 0000-0002-6487-2671
Qiwei YuLewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey 08544, USA.ORCID 0000-0003-0610-3484
Rich PangPrinceton Neuroscience Institute, Princeton University, Princeton, New Jersey 08544, USA.
William BialekJoseph Henry Laboratories of Physics, Princeton University, Princeton, New Jersey 08544, USA.ORCID 0000-0002-7823-3862
Stephanie E PalmerDepartment of Organismal Biology and Anatomy, University of Chicago, Chicago, Illinois 60637, USA.ORCID 0000-0001-6211-6293

Funding

Coarse-graining approaches to networks, learning, and behaviorR01EB026943 · NIBIB · UNIVERSITY OF CHICAGO · PI BIALEK, WILLIAM, PALMER, STEPHANIE E · 2018 to 2020
$1.1M
NIBIB NIH HHS R01 EB026943
6 · The paper itself

Abstract

Maximum-entropy methods provide a principled path connecting measurements of neural activity directly to statistical physics models, and this approach has been successful for populations of

Identifiers

PMID42569757
PMCPMC13451037

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.